Nektar.AI Exits Stealth Mode

Nektar.AI supports automated activity capture and CRM sync across the full customer lifecycle.

After two years in stealth mode, Revenue Operations solution provider Nektar.AI was unveiled earlier this month.  Nektar looks to solve the “CRM data leakage” problem whereby critical lead, contact, and opportunity data is omitted or decays.  For example, Nektar recognizes meeting attendees missing from the CRM and automatically creates contact records that include email, direct dial phone, title, and buying committee role.  Out-of-date or missing data negatively impacts both the sales process and operational functions such as analytics, automated recommendations, and pipeline forecasting.

Nektar offers a no-code platform that applies natural-language processing against email, calendar, chat, and social touchpoints, capturing revenue activity data across the full customer lifecycle and syncing it with the CRM.  Automated activity capture improves rep productivity, allowing sales professionals to focus on selling instead of data entry and updating.

“Sales teams depend on their CRM data to gain insights into team productivity, pipeline insights, and revenue forecasting.  Despite a CRM being an important system of record for modern go-to-market teams, it still grapples with the problem of poor user adoption and missing data.  As per estimates, 40-50% of sales activity data remains missing from a CRM, while 27% of the data that’s available in a CRM decays every month.  This leads to major data and productivity leakage,” stated the firm.

Furthermore, deals are becoming increasingly complex, with larger buying committees and sales teams communicating across an expanding array of sales channels.  While most of these conversations are now digital, they take place across disparate platforms and channels, resulting in data fragmentation.  Nektar’s mission is to collect this fragmented intelligence and feed it into the CRM, making it available to the revenue team without requiring sales resources to key this intelligence.

“There are a lot of reporting and analytics solutions out there.  Other solutions have been investing primarily in the downstream problem with respect to visibility and analytics, an important problem to solve.  But the core problem actually starts upstream, which is where activities are taking place and where data is being generated.  A lot of that data doesn’t make its way into CRM, which actually results in downstream problems.  If there’s poor data in, you will have poor insights available,” explained CEO Abhijeet Vijayvergiya to GZ Consulting.

“We found our product-market fit when we found that more than 50% of critical revenue activity data is not going into CRM,” continued Vijayvergiya.  “This data leak results in productivity leaks, and that results in revenue leaks.”

Furthermore, as firms make staffing cuts, “they’re trying to do more with less” and losing implicit knowledge that never made its way into the CRM.  Nektar allows companies to recover much of this lost activity and contact intelligence, boosting a firm’s ability to manage revenue operations during a recession.

“There are tools like Gong and Clari and some other forecasting solutions which provide good insights,” expanded Vijayvergiya on Nektar’s value proposition.  But these systems are not resolving the data leakage problem. 

Nektar claims 95% accuracy in its data capture and syncing processes.  The service can go live in ninety minutes and begins providing time to value in three days as it gathers both historical data missing from the CRM and populates it with ongoing activity capture. 

Nektar operates in the background, collecting and syncing data.  Thus, there are no training sessions or additional UIs to learn.  Sales reps do not need to toggle to other platforms, and their data entry work is significantly reduced.

“Nektar plugs the CRM data leakage without a user lifting their finger.  We basically eliminate the need for user adoption and give all the time back to salespeople to go and sell while relieving their administrative burden,” said Vijayvergiya.

While there have been third-party solutions to populate and enrich account and contact data records for over a decade (e.g., Dun & Bradstreet, ZoomInfo), these vendors were blind to the demand unit unless a sales rep entered all members.  Nektar is complementary to third-party DaaS providers, Revenue Intelligence vendors (e.g., Clari, Revenue Grid), Conversational Sales (e.g., Gong, Chorus), and business intelligence vendors (e.g., Tableau).

“We are aware that some of these solutions have their own activity capture system, but most of their activity capture solutions work in silos for certain sets of users who adopt their solution,” continued Vijayvergiya.  “Users are not adopting the solution, or data loss happens anyway.   A solution which we replace, more often than not, is Salesforce Einstein Activity Capture.”

Nektar supports email and domain exclusion lists to prevent mining confidential information (e.g., legal, investor relations, partner development).

Nektar is generally available as a native Salesforce solution, with HubSpot and Microsoft Dynamics on the roadmap.  In addition, all of its system integrations are native, providing higher quality and performance.

Nektar.AI closed a $6 million seed round last summer, raising its total funding to $8.1 million.  The round was led by B Capital Group, with Nexus Venture Partners, 3One4 Capital, and angel investors also joining.

Nektar has not disclosed pricing, but it is per user per month with SaaS-based pricing billed quarterly or annually.

Nektar is a fully remote company with 32 employees across seven countries with plans to hit fifty employees by the end of this year.  Although emerging from stealth, it already supports over 1,500 users. 

Nektar’s goal through year-end is to focus on its go-to-market strategy and North American hiring.

Nektar activity tracking at the account level

Data capture as an AI tool is becoming increasingly important. It probably isn’t a standalone offering but an underlying capability for populating the CRM with harvested digital intelligence, monitoring buyer engagement, and building out the buying committee. As such, it is core to both CRM data enrichment and revenue intelligence.

I have seen a series of data capture announcements from vendors of all sizes: big (Microsoft Viva Sales), medium (People.AI, Introhive), and small (e.g., Nektar, Winn.AI). I will be covering People.AI and Winn.AI later this week.

Vainu for HubSpot

Vainu for HubSpot Data Mapping rules.

Yesterday, I posted about Vainu’s new Global Database. The firm also announced its Vainu for HubSpot connector for matching and enriching company data against its global reference database.

“Most sales and marketing teams want to be data-driven.  They want to run ABM campaigns, apply modern lead scoring models, and automate many parts of the sales process.  SalesOps and Marketing Ops professionals are there to facilitate all that, but there’s one common challenge they’re facing: CRM data is messy and outdated,” observed Vainu co-founder Mikko Honkanen.  “With that struggle in mind, we thought it would be a good time to launch a new HubSpot connector at the same time that we’re launching Vainu Global…so that it’s easy for companies using HubSpot to get their CRM data cleaned, updated, and enriched.”

As companies are being matched against Vainu’s new global database, not registered Nordic filings, the match field is URLs, not business IDs or VATs.  With forms, contacts are matched against email domains.  If a company is not already in HubSpot, new Accounts are created, and the Contacts are associated with the new record.

“This means it works very well with HubSpot CRM, because domain is often the company property that a business will have for almost all of the company records they have in their CRM, which means that it’ll be easier to match the companies in HubSpot to our database,” contended Honkanen.

During beta testing, match rates were as high as 99%.  For non-matched records, the firm offers on-demand matching against missing domains.  If they are valid domains, Vainu adds profiles to its company directory.

Along with standard firmographics, account enrichment includes Vainu’s Custom Industry segments, global web traffic ranking, and Vainu segments (e.g., website keywords or phrases).  Profiles generally have four to eight industry labels, helping with targeting.

Other fields include technographics and domain redirect information.  Redirects are often implemented after acquisitions or rebrands and are useful for assigning contacts.

Vainu for HubSpot Send to CRM

Vainu offers a field mapper for assigning Vainu data to HubSpot and setting update rules.  For example, admins can set field update logic to always update, update if null, or never update.  Vainu custom fields that are not in HubSpot are automatically created.  Along with companies, admins can map contacts, tasks, notes, and deals. 

Thus, admins can build a campaign and upload it to HubSpot with task assignments.  The inclusion of tasks and notes helps specify campaign details, such as recommended collateral and case studies, with the Vainu Custom Industry and Technology Intelligence assisting with messaging.

If companies do not exist in HubSpot, Account records are created.  If they exist, then the existing records are enriched. 

By default, HubSpot does not overwrite current account owners.

Updates can be performed on a scheduled basis or executed as a one-time batch operation. 

Vainu intelligence with tasks and notes displayed in HubSpot.

Vainu Launches Global Database

Vainu Global Database Attributes

European Sales Intelligence vendor Vainu unveiled its new Global Database this week, a domain-based company dataset spanning over 65 million companies.  The database was built through web-crawling and includes standard firmographics, technographics, Vainu Custom Industry Codes, social links (Facebook and LinkedIn), and web-based insights (keywords and phrases that describe the company). 

Domains are mapped to headquarters locations, with additional locations captured during the site crawl and displayed as part of the profile.  A countries of operation field helps with market entry planning (e.g., which companies in our ICP have operations in specific countries?).  Vainu also captures website languages, helping determine which markets companies are targeting.

“If you’re selling a product or service where the buying decision is made on a business unit/regional level, having this type of data in your CRM is crucial,” argued co-founder Mikko Honkanen.  “It helps your sales reps to pick upsell and cross-sell opportunities and in general, makes it easier to maximize the revenue potential of your customer portfolio.”

“Unfortunately, finding good data for regional offices has been challenging in the past,” continued Honkanen.  “Most companies will only list their main office on their social media accounts, and it’s been difficult for salespeople to manually add office data from company websites to their business systems due to the limitations in the availability of data properties.”

Filtering with Vainu’s proprietary industry codes and associated Confidence Scores.

Vainu offers over 900 proprietary industry codes, including emerging industries such as SaaS and Artificial Intelligence not available in other taxonomies.  When screening, the system defaults to high-level confidence, but users can more broadly search by accepting companies with lower industry tagging confidence.  In addition, users may select one or multiple categories, employ Boolean logic (e.g., SaaS AND Executive Recruitment), and modify their selects with web-based insights.

The crawler and platform UX are English only.

Discrete sizing data is not provided, with companies mapped to five employee ranges.  Vainu employs an “ordinal regression and classification approach” to its model that factors in web traffic, the number of office locations, detected web technologies, mentions of specific key phrases, etc.

Honkanen argues that its methodology may be off by one size band but is unlikely to make large errors.  “Our own internal testing indicates that our model generally outperforms other employee count models, but it truly shines when it comes to minimizing the large, important mistakes.  What that means is that it might be difficult for the model to choose between 51-200 and 201-1,000 if the company has roughly 200 employees, but it has an easy time avoiding big and important mistakes, such as enterprise companies being classified as micro companies.  In other words, our model still makes mistakes, but those mistakes are often small in magnitude, i.e., the model might predict the nearest neighbor.”

Vainu has been building and tuning the database for over a year, helping it distinguish between product sites (e.g., Tide) and company sites (e.g., Proctor & Gamble).  It is growing at 100,000 companies per day and recrawls sites every sixty days.  Users can set up saved searches that identify new companies, upload them to HubSpot, and alert the sales rep.

Company data is available through a web-based platform, API, CSV downloads, and connectors (HubSpot today, with Salesforce and Microsoft Dynamics 365 on the Global Database roadmap). 

Users can also upload lists of domains for matching and enrichment.  When downloading data, they specify file formats, controlling which fields to download and their order.

As they offer a LinkedIn field, users can quickly create and upload LinkedIn Matched Audiences to the LinkedIn Campaign Manager with high match rates.

The database does not contain contacts, but Honkanen argues that Vainu’s company data is superior to firmographics from other services.

Honkanen provided several reasons for not offering contacts, “We don’t want to be a vendor that provides bulk contact data…We don’t want to promote salespeople to do spam.  Also, it is very challenging to do that in a GDPR-compliant way.”

Instead, the company wants to promote “smart, Account Based Marketing” that supports very specific industry and keyword screening and LinkedIn audience campaigns.  From the LinkedIn Campaign Manager, users can target by persona.  Users can also match against existing HubSpot contacts with pre-existing consent tied to Vainu-enriched firmographics.

“If you’re looking for a combination of high-quality firmographic and website-based insights, we’ve got you covered,” blogged Vainu Marketer Nikolai Bang.  “Our global data offering includes numerous important data points, such as location, industry, company size, technologies, website keywords, and website traffic, that, according to our customers who have tested several offerings, other vendors cannot provide at a similar quality.”

While other databases, including Vainu’s Nordics database, are built around business ids, the global database is built around domains, with the firm capturing multiple locations related to domains.  Business ids are preferred for KYC and credit scenarios as the data is tied to legal ids, but domain data matches well against CRMs and emails.

Vainu contends that domain-keyed databases are better for ICP/TAM analysis as subsidiaries and branches aren’t double counted, providing a more accurate view of market opportunity.  Vainu claims that ICPs built using Vainu Custom Industry codes and website-based insights during beta testing consistently achieved 90% accuracy.

The Global Database resides on a new platform and is available as a distinct product with separate licensing and administration from its Nordic registered-data services.

Pricing starts at €12,000 per annum, with a one-time setup fee starting at €1,000.  Instead of seat-based pricing, Vainu is pricing based on the number of records uploaded or maintained.

Vainu Company Profile

Vainu Resources

ZoomInfo Expands its Technographics

ZoomInfo, which began as a technology sales intelligence service, has expanded its technographic intelligence to more than 30 million global companies.  The technographic dataset now spans 300 million company/tech pairings, whether that is a technology, platform, or programming language.

The firm, which has recently focused on sales and marketing enablement technology (e.g., Conversational Sales, Chatbots, Sales Engagement, Recruitment/HR) and Operations, has been quietly expanding its content coverage with announcements concerning company coverage and technographics in the past few weeks.

“Knowing which technologies your prospects use before you even pick up the phone gives sellers a tremendous head start,” said Kirti Patel, Senior Director of Engineering at ZoomInfo.  “With today’s economic headwinds, sales teams are looking for every opportunity to increase efficiency, and having access to a prospect’s tech stack can transform your go-to-market engine.”

ZoomInfo’s technographics intelligence is derived from over twenty data sources, including company websites, job postings, and customer testimonials.  Its taxonomy covers over 30,000 technologies.

ZoomInfo claims that nearly 90% of its active tech-to-company pairings have been updated within the past three months.

Technographics assists with prospecting, lead and account scoring, look-a-like modeling, and market analysis (e.g., Technology Market Share, ICP, and TAM).  It is also common for firms to target customers of partners for complementary pitches and competitors for takeaways. ZoomInfo supports alerting when technologies are added or dropped from prospects’ tech stacks.  In addition, its Workflow module automates sales and marketing outreach.

ZoomInfo provided a pair of ZoomInfo SalesOS screenshots to GZ Consulting with functional descriptions concerning their technographics capabilities:

Technographic Alerts: “Customers can subscribe to individual technologies to get alerts on what companies are Adding/Dropping/Discovering that technology. For Adds, we know the company recently began using that technology, whereas, for Discoveries, we believe the company has been using the technology for a while, but our systems are just discovering it for the first time.”

Company Specific Profile: “This image is just one technology that ZoomInfo uses. It shows the date of the last time we have seen evidence that ZoomInfo uses machine learning technology. We can only view one technology category at a time on a company’s profile. You’ll see to the left of the image all of the technology categories that we have ZoomInfo technologies for.  You can hover over each to get the date of the last evidence.”

ZoomInfo Hits 100M Company Profiles

ZoomInfo continues to build out its company database, tripling its coverage over the past year.  Its most recent content additions are small firms not found on the Internet.  The firm was able to treble its company coverage after acquiring Everstring in late 2020. The expanded coverage improves a core data asset the firm deploys across its four cloud services.

“Now ZoomInfo customers have broader visibility into their total addressable market.  Teams using SalesOS can build more targeted company lists based on characteristics of their ideal customers, driving more accurate segmentation,” stated the firm.  “Users of ZoomInfo’s OperationsOS product will experience increased match rates and can build out more robust and accurate company hierarchies.  MarketingOS users will be able to reach wider audiences through their campaigns and identify more traffic visiting their websites.  And customers of TalentOS will be able to find more qualified candidates in a challenging hiring environment.”

ZoomInfo offers a corporate family tree display that allows users to expand/collapse nodes and drill down to subsidiaries.

Data was sourced from state registries, business registry filings, and licensed data.  ZoomInfo also addressed a long-standing gap in its coverage with 35 million “non-headquarter company locations” (e.g., branches).  Branches are crucial for accurately sizing markets, routing leads, and performing lead-to-account mapping.  For example, if an inbound branch lead, particularly one with a different name than its parent, is not mapped to the parent HQ, it is likely to be misrouted or ignored.

Every ZoomInfo company record contains revenue, headcount, and industry mappings (NAICS and US SIC87).

ZoomInfo also continues to build out its contact database, reaching 220 million active contacts, with 150 million emails, 65 million direct dials, and 50 million mobile numbers.

“Our enhanced data pipeline brings together the best of both worlds: access to more companies and the assurance that this new information is accurate,” said Kirti Patel, Senior Director of Data Engineering at ZoomInfo.  “This key expansion of our data allows our customers to access a vast market opportunity, especially among small businesses that are often harder to reach.”

In other news, ZoomInfo has grown its Shoreditch (London) sales team to over 100 reps.  Two years ago, all European sales were managed by a six-person team out of the US eastern time zone that began placing calls to Europe at 3 AM.


ZoomInfo also announced expanded technographics for targeting prospects that deploy competitive or complementary offerings.

Matchbook AI Funding

Matchbook AI, which offers External Data and Data Hygiene solutions to enterprise clients, has announced a $3 million seed extension.  It previously received $1.7 million in seed and friends and family funding.

Matchbook was founded in 2018 but operated as a garage project for a couple of years before being incorporated.  CEO Rushabh Mehta had the idea for the Matchbook Data Hub while an industry evangelist and initially built the solution with Dun & Bradstreet data.  The Data Hub provides a configurable, hierarchical matching service that matches and enriches records with a single API call.  Both batch and real-time matching are supported, with cascading and waterfall matching processes.  In addition, a rules engine allows customers to construct bespoke data cleansing and filtering rules specific to various business units and use cases.  The Data Hub will be powered by Snowflake.

The system can use other identifiers such as domains or emails if the account cannot be matched by name and address.  In addition, the system manages deduplication and prevents creating duplicate records when onboarding accounts. The solution can also support more complex matching scenarios to allow for verification checks and multi-attribute matching.

“I can immediately see if I already have an existing relationship with that account,” Mehta explained to GZ Consulting.  “Just because I keyed in the name incorrectly or a previous account had a different address for that same company, I should still be able to identify and say, ‘Hey, no, it’s the same company to the same account.’”

The Data Hub also manages information for enterprise clients with multiple CRMs, helping “provide that visibility across CRMs, across ERPs, or CRM and ERP.”  Thus, Matchbook can identify whether “there is already an existing relationship within the organization with that particular entity” through third-party identification.  Furthermore, matching identifies parent-sub relationships tied together by D-U-N-S numbers.

According to Mehta, customers want controlled updates to their CRM or ERP, not real-time updates.  They also want to control which fields are updated with the data hub keeping “everything mastered in one place” with the intelligence accessible to the organization.

Matchbook AI’s data partners and supported platforms

Along with Dun & Bradstreet’s data sets (e.g., companies, contacts, hierarchies, beneficial ownership, D-U-N-S identifiers, technographics, competitors, company news, and credit and supplier risk profiles), Matchbook AI provides third-party reference data from ZoomInfo, Demandbase, Moody’s, Experian, Melissa, and Google.  The service also includes sanctions and terrorist watchlist data for compliance use cases.

The Data Hub operates as a centralized external data repository for maintaining data quality and standardizing data across platforms, including Salesforce, Snowflake, SAP, Informatica, Microsoft, Oracle, Certa, and Reltio.  The Data Hub supports a broad set of processes and departments, with sales, marketing, finance, IT, logistics, compliance, legal, and supplier management use cases. It also plays a critical role in MDM use cases through integrations with Reltio and others.

Matchbook claims implementations between two days and two months, significantly faster than its competitors.  Furthermore, as a DaaS solution, it is 90% less expensive than in-house solutions.  It also claims a 75% savings on expenses related to maintaining a data stewardship team due to “improved data quality and automated management.”

VP of Sales & Marketing Wesley Billingslea described a recent dinner with a Fortune 500 CIO who described Matchbook AI as “quite strategic and pervasive because we go across departments,” whereas “most MDM projects sit in the IT organization.”  This approach “empowers” teams across the organization with superior data and a plug-and-play solution.

Matchbook focuses on enterprise clients, with 59% of its customers in the Fortune 500.  It takes a land-and-expand approach that proves itself in one department or on one platform and then extends to others.  Contracts are usually written for a single year and then converted to multi-year contracts a year later.  The strategy has resulted in a 118% net retention rate and a projected ARR increase of 220% this year.

“As we gear up our sales and marketing efforts, we are confident that we will soon achieve $3.5 million in annual recurring revenue (ARR) with Current ARR of $1.85 million,” said Mehta.  “Data should be trusted, enriched, and always ready.  I feel very confident in our approach as we take these next steps and help companies understand their data DNA in this age of intelligent business.”

Matchbook claims an impressive LTV/CAC ratio greater than 12, an important indicator of stickiness, value, and an efficient go-to-market approach.

Mehta noted that it is just entering a large market with a rapidly expanding TAM.  According to MarketsandMarkets, data cleansing and global master data management were an $11.3 billion market in 2020, growing to $27.9 billion by 2025 (19.8% CAGR).

“Our value proposition to an MDM implementation can mean the difference between success and failure,” said Mehta.

Pricing is based on a records-under-management model, providing a predictable budget line to companies.  Implementations range from 50,000 to 100 million records. Matchbook has grown to 51 employees in the Americas and Asia.  The bulk of its R&D is conducted in Asia.

Saleo Live Demo Platform

Demo Experience Platform vendor Saleo launched its Saleo Live platform which transforms “existing demo environments into data-complete, relevant demos that help pre-sales and sales teams turn more deals into ‘closed won.’”

Saleo noted a series of demo platform issues that it addresses, including “bad demo data, unstable demo environments, generic use cases, costly demo prep time, and expensive engineering investment in supporting the demo environment.” Furthermore, sales engineers and solutions consultants find it challenging to customize demos by persona and industry.

“The north star with Saleo and Saleo Live has always been resolute – we believe that software companies should be able to demo their live native SaaS product with full control and complete reliability. Anything else is unauthentic. Fake screenshots, HTML screen capture, and click-through demos lead to a disingenuous buying experience from pre-sales. Saleo is the only platform in the market that empowers full control of every element in a live SaaS product; the end result is a transformed demo experience that leads to reduced pre-sales costs and higher win rates.”

Saleo CEO Justin McDonald

Saleo Live lets sales organizations define and share no-code custom demos “within minutes.” Sales engineers can quickly customize text, tables, images, graphs, and metrics. New features include Single Sign On, a “more sophisticated modeling engine to support advanced graph permutations,” an updated UX (UX), advanced user permissioning, and a new token system that scales personalization.

“The reaction to our latest release has been incredibly positive from Sales & Product Marketing teams,” said Saleo CPO Daniel Hellerman. “The reaction to Saleo from the pre-sales market has been overwhelming. We are solving an age-old problem with a unique architecture that puts sales engineers at the forefront of the solution. Screenshots and click-throughs from existing solutions have been prohibitive, and limit sales teams to on-rails demos, where they can’t showcase their genuine application; Saleo Live has unleashed their potential.”

Customers include Salesloft, Terminus, and Drift.